Senior / Staff Applied AI Engineer

Since 2013, Techery has been bridging the gap between business vision and technology. As a product and consulting company, we focus on building our own products that are both technologically advanced and tailored to meet real-world needs. Innovation is at our core, and we are increasingly leveraging the power of AI to develop cutting-edge features and explore new possibilities within our product portfolio. Beyond our product development, we act as a consulting software company for non-tech clients and are in full charge of solving their challenges. Whether it's addressing complex issues or turning innovation into reality, our commitment ensures that the best visions are fully realized, providing clients with comprehensive solutions that drive success. Beacon is a core product within Treel OS — an AI-powered data analyst and sales-strategy assistant that connects to enterprise data, services, and workflows. Beacon goes beyond chat: it generates persistent dashboards, analytical views, reports, workflows, and on-demand interfaces tailored to a specific company, role, user, and objective. We're looking for a Senior or Staff-level engineer who can turn ambiguous AI product problems into production systems, validate them with evidence, and improve quality, latency, and cost through hands-on engineering. Key Responsibilities Design and implement agent execution workflows with structured, validated model outputs Build semantic routing and complexity-classification systems across skills, data sources, and models Develop classifiers using BERT-style models, embeddings, rules, and ensembles Implement multi-turn context handling and state/context-retrieval mechanisms Build model-independent interfaces across OpenAI, Google, and open-weight models Create synthetic-data generation and validation pipelines Fine-tune and evaluate small models and classifiers Build grounding, provenance, and factuality/claim-validation mechanisms Create automated offline and online evaluation systems Analyze production failures and convert them into product improvements Optimize quality, latency, and inference cost Write production backend code and tests, contributing to architectural decisions through implementation Skills, Knowledge and Expertise Substantial experience building production backend systems under ambiguous product requirements Hands-on experience implementing LLM-powered applications beyond prompt prototypes (structured outputs, tool execution, agent orchestration) Experience with retrieval, classification, ranking, or semantic routing Background in classical machine learning and modern language models Experience with embeddings and vector-based systems Familiarity with supervised fine-tuning, LoRA, adapters, or distillation Experience with evaluation design and model error analysis Experience with synthetic-data generation Strong backend engineering skills in TypeScript, Rust, or another strongly engineered ecosystem Practical, disciplined experience working with coding agents (codebase exploration, task decomposition, test generation, large refactors, failure investigation)